Recommender System
2022-07
Traditional recommender systems rely on historical user data, but session-based recommender systems focus solely on a user’s interactions within a single session—ideal for anonymous or new users. In session-based recommenders, continuous parameter tuning is crucial, and this is where an AutoML-based framework can be highly effective.
Although I wasn’t a primary contributor to this project, I provided support to my friend AmirReza, and he graciously included me as a co-author on the paper.